#!/usr/bin/env python2
# -*- coding: utf-8 -*-
# 导入必要的软件包
import cv2
'''
# 创建参数解析器并解析参数
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
args = vars(ap.parse_args())
 
# 如果video参数为None，那么我们从摄像头读取数据
if args.get("video", None) is None:
    camera = cv2.VideoCapture(0)
    time.sleep(0.25)
 
# 否则我们读取一个视频文件
else:
    camera = cv2.VideoCapture(args["video"])
 
# 初始化视频流的第一帧
"../"
"../FFOutput/04.avi"
"../FFOutput/05.avi"
"../bike.avi"
"../fucing.avi"      
"../FFOutput/02.avi" "disturbing"
"../FFOutput/07.avi" "quick movement"
"../FFOutput/11.avi" 
"../FFOutput/12.avi" "people too much"
"../FFOutput/13.avi" "no symbolic object"
"../FFOutput/14.avi" "no symbolic object"
"../FFOutput/18.avi"
'''
class Point(object):
    def __init__(self,x,y):
        self.x=x
        self.y=y
    pass

class objectbbox(object):
    total=0
    def __init__(self,boundingbox):
        self.bbox=boundingbox
        center=Point(int(boundingbox[0]+boundingbox[2]/2),int(boundingbox[1]+boundingbox[3]/2))
        self.centerpositions=[center]
        self.number=0
        self.nextposition=Point(-1,-1)
        self.existing=True
        
    def equalto(self,boundingbox):
        center=Point(int(boundingbox[0]+boundingbox[2]/2),int(boundingbox[1]+boundingbox[3]/2))
        rate=0.2
        if center.x<self.nextposition.x*(rate+1) and center.x>self.nextposition.x*(1-rate) and center.y<self.nextposition.y*(1+rate) and center.y>self.nextposition.y*(1-rate):
            return True
        else:
            return False
    
    def updateto(self,boundingbox):
        self.bbox=boundingbox
        center=Point(int(boundingbox[0]+boundingbox[2]/2),int(boundingbox[1]+boundingbox[3]/2))
        self.centerpositions.append(center)
        self.existing=True
    
    def predictnextposition(self):
        numpositions=len(self.centerpositions)
        if numpositions==1:
            self.nextposition.x=self.centerpositions[-1].x
            self.nextposition.y=self.centerpositions[-1].y
            
        elif numpositions==2:
            deltaX=self.centerpositions[1].x-self.centerpositions[0].x
            deltaY=self.centerpositions[1].y-self.centerpositions[0].y
            self.nextposition.x=self.centerpositions[-1].x+deltaX
            self.nextposition.y=self.centerpositions[-1].y+deltaY
            
        elif numpositions==3:
            sumofxchanges=(((self.centerpositions[2].x-self.centerpositions[1].x)*2)+
                           ((self.centerpositions[1].x-self.centerpositions[0].x)*1))
            deltaX=int(round(float(sumofxchanges)/3.0))
            sumofychanges=(((self.centerpositions[2].y-self.centerpositions[1].y)*2)+
                           ((self.centerpositions[1].y-self.centerpositions[0].y)*1))
            deltaY=int(round(float(sumofychanges)/3.0))
            self.nextposition.x=self.centerpositions[-1].x+deltaX
            self.nextposition.y=self.centerpositions[-1].y+deltaY            
            
        elif numpositions==4:
            sumofxchanges=(((self.centerpositions[3].x-self.centerpositions[2].x)*3)+
                           ((self.centerpositions[2].x-self.centerpositions[1].x)*2)+
                           ((self.centerpositions[1].x-self.centerpositions[0].x)*1))
            deltaX=int(round(float(sumofxchanges)/6.0))
            sumofychanges=(((self.centerpositions[3].y-self.centerpositions[2].y)*3)+
                           ((self.centerpositions[2].y-self.centerpositions[1].y)*2)+
                           ((self.centerpositions[1].y-self.centerpositions[0].y)*1))
            deltaY=int(round(float(sumofychanges)/6.0))
            self.nextposition.x=self.centerpositions[-1].x+deltaX
            self.nextposition.y=self.centerpositions[-1].y+deltaY  
            
        elif numpositions>=5:
            sumofxchanges=(((self.centerpositions[-1].x-self.centerpositions[-2].x)*4)+
                           ((self.centerpositions[-2].x-self.centerpositions[-3].x)*3)+
                           ((self.centerpositions[-3].x-self.centerpositions[-4].x)*2)+
                           ((self.centerpositions[-4].x-self.centerpositions[-5].x)*1))
            deltaX=int(round(float(sumofxchanges)/10.0))
            sumofychanges=(((self.centerpositions[-1].y-self.centerpositions[-2].y)*4)+
                           ((self.centerpositions[-2].y-self.centerpositions[-3].y)*3)+
                           ((self.centerpositions[-3].y-self.centerpositions[-4].y)*2)+
                           ((self.centerpositions[-4].y-self.centerpositions[-5].y)*1))
            deltaY=int(round(float(sumofychanges)/10.0))
            self.nextposition.x=self.centerpositions[-1].x+deltaX
            self.nextposition.y=self.centerpositions[-1].y+deltaY              
            
        else:
            print "should never get here"        

objects=[]
"../"
"../FFOutput/04.avi"
"../FFOutput/05.avi"
"../bike.avi"
"../fucing.avi"      
"../FFOutput/02.avi" "disturbing"
"../FFOutput/07.avi" "quick movement"
"../FFOutput/11.avi" 
"../FFOutput/12.avi" "people too much"
"../FFOutput/13.avi" "no symbolic object"
"../FFOutput/14.avi" "no symbolic object"
"../FFOutput/18.avi"
camera=cv2.VideoCapture("../FFOutput/05.avi")
firstFrame = None
if False == camera.isOpened():  
    print 'open video failed'  
else:  
    print 'open video succeeded'    
(grabbed, frame) = camera.read()
# 遍历视频的每一帧
while True:
    # 获取当前帧并初始化occupied/unoccupied文本
    
    (grabbed, frame) = camera.read()
    text = "Unoccupied"
    
    # 如果不能抓取到一帧，说明我们到了视频的结尾
    if not grabbed:
        print 'not grabbed'   
        break
 
    # 调整该帧的大小，转换为灰阶图像并且对其进行高斯模糊
    #frame = imutils.resize(frame, width=500)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)
 
    # 如果第一帧是None，对其进行初始化
    if firstFrame is None:
        firstFrame = gray
        continue
    # 计算当前帧和第一帧的不同
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
 
    # 扩展阀值图像填充孔洞，然后找到阀值图像上的轮廓
    thresh = cv2.dilate(thresh, None, iterations=2)
    (binary,cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    # 遍历轮廓
    for c in cnts:
        # if the contour is too small, ignore it
        #if cv2.contourArea(c) < args["min_area"]:
        #    continue
 
        # compute the bounding box for the contour, draw it on the frame,
        # and update the text
        # 计算轮廓的边界框，在当前帧中画出该框
        contouroccupied=False
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = "Occupied"
        if w>10 and h>10:
            for oneobject in objects:
                if oneobject.equalto((x,y,w,h)):
                    oneobject.updateto((x,y,w,h))
                    contouroccupied=True
        if not contouroccupied:
            objects.append((objectbbox((x,y,w,h))))

    i=0
    for oneobject in objects:
        if oneobject.existing==False:
            del objects[i]
        oneobject.predictnextposition()
        oneobject.existing=False
        i+=1
                    
    print len(cnts)
   # 显示当前帧并记录用户是否按下按键
    cv2.imshow("Security Feed", frame)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Frame Delta", frameDelta)
    key = cv2.waitKey(100) & 0xFF
 
    # 如果q键被按下，跳出循环
    if key == ord("q"):
        break
 
# 清理摄像机资源并关闭打开的窗口
camera.release()
cv2.destroyAllWindows()